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Classification of Abnormal Gaits with Machine Learning Algorithms using Sensor-Inherited Insoles.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The digital health industry's interest in gait analysis has driven research into sensor-enabled insoles for practical, everyday gait monitoring. Traditional methods, such as 3D motion capture systems, are costly and time-consuming. To address this, w...

Deep Learning-Based Subject Independent Human Activity Recognition using Smart Lacelock Data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Human Activity Recognition (HAR) field is rapidly growing and the classification of human activities based on sensor data is crucial for applications in healthcare, rehabilitation and numerous other sectors. In this paper we use a novel device and at...

StepGAN: Gait Feature Extraction Using Generative Adversarial Networks for Footstep Recognition.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Pressure recordings of footsteps during walking can offer a convenient biometric recognition method for applications in security, forensic analysis, and health monitoring. However, footsteps can exhibit high variability due to a complex interplay of ...

Comparison of the Accuracy of Ground Reaction Force Component Estimation between Supervised Machine Learning and Deep Learning Methods Using Pressure Insoles.

Sensors (Basel, Switzerland)
The three Ground Reaction Force (GRF) components can be estimated using pressure insole sensors. In this paper, we compare the accuracy of estimating GRF components for both feet using six methods: three Deep Learning (DL) methods (Artificial Neural ...

Classification of 3D shoe prints using the PointNet architecture: proof of concept investigation of binary classification of nike and adidas outsoles.

Forensic science, medicine, and pathology
Shoe prints are one of the most common types of evidence found at crime scenes, second only to fingerprints. However, studies involving modern approaches such as machine learning and deep learning for the detection and analysis of shoe prints are qui...

Multi-Activity Step Counting Algorithm Using Deep Learning Foot Flat Detection with an IMU Inside the Sole of a Shoe.

Sensors (Basel, Switzerland)
Step counting devices were previously shown to be efficient in a variety of applications such as athletic training or patient's care programs. Various sensor placements and algorithms were previously experimented, with a best mean absolute percentage...

Leather-Based Shoe Soles for Real-Time Gait Recognition and Automatic Remote Assistance Using Machine Learning.

ACS applied materials & interfaces
Real-time monitoring of gait characteristics is crucial for applications in health monitoring, patient rehabilitation feedback, and telemedicine. However, the effective and stable acquisition and automatic analysis of gait information remain signific...

A machine learning driven computationally efficient horse shoe shaped antenna design for internet of medical things.

PloS one
With bio-medical wearables becoming an essential part of Internet of Medical things (IoMT) for monitoring the health of workers, patients and others in different environments, antenna play a pivotal role in such wearables. In this communication, a no...

Parametric cushioning lattice insole based on finite element method and machine learning: A preliminary computational analysis.

Journal of biomechanics
The cushioning performance of insole has always been a critical consideration in its design. While the development of intelligent methods and the emergence of additive manufacturing (AM) technology have enhanced design freedom and convenience, a stan...

Deep self-organizing map neural networks improve the segmentation for inadequate plantar pressure imaging data set.

Network (Bristol, England)
This study introduces a deep self-organizing map neural network based on level-set (LS-SOM) for the customization of a shoe-last defined from plantar pressure imaging data. To alleviate the over-segmentation problem of images, which refers to segment...